diff --git a/doc/python/horizontal-bar-charts.md b/doc/python/horizontal-bar-charts.md
index 1daf8c6505..1c3c9f5078 100644
--- a/doc/python/horizontal-bar-charts.md
+++ b/doc/python/horizontal-bar-charts.md
@@ -91,8 +91,8 @@ fig.add_trace(go.Bar(
name='SF Zoo',
orientation='h',
marker=dict(
- color='rgba(246, 78, 139, 0.6)',
- line=dict(color='rgba(246, 78, 139, 1.0)', width=3)
+ color='hotpink',
+ line=dict(color='deeppink', width=3)
)
))
fig.add_trace(go.Bar(
@@ -101,8 +101,8 @@ fig.add_trace(go.Bar(
name='LA Zoo',
orientation='h',
marker=dict(
- color='rgba(58, 71, 80, 0.6)',
- line=dict(color='rgba(58, 71, 80, 1.0)', width=3)
+ color='dimgray',
+ line=dict(color='black', width=3)
)
))
@@ -155,16 +155,15 @@ fig.show()
### Color Palette for Bar Chart
+This bar chart uses a sequential palette to show gradations of responses. Additional color options for sequential palettes are available at [The Urban Institute](https://urbaninstitute.github.io/graphics-styleguide/#color) and [Colorbrewer](https://colorbrewer2.org/#type=sequential)
+
```python
import plotly.graph_objects as go
top_labels = ['Strongly
agree', 'Agree', 'Neutral', 'Disagree',
'Strongly
disagree']
-colors = ['rgba(38, 24, 74, 0.8)', 'rgba(71, 58, 131, 0.8)',
- 'rgba(122, 120, 168, 0.8)', 'rgba(164, 163, 204, 0.85)',
- 'rgba(190, 192, 213, 1)']
-
+colors = ['DarkBlue', 'MediumBlue', 'DarkSlateBlue', 'mediumpurple', 'thistle']
x_data = [[21, 30, 21, 16, 12],
[24, 31, 19, 15, 11],
[27, 26, 23, 11, 13],
@@ -185,7 +184,7 @@ for i in range(0, len(x_data[0])):
orientation='h',
marker=dict(
color=colors[i],
- line=dict(color='rgb(248, 248, 249)', width=1)
+ line=dict(color='ghostwhite', width=1)
)
))
@@ -204,8 +203,8 @@ fig.update_layout(
zeroline=False,
),
barmode='stack',
- paper_bgcolor='rgb(248, 248, 255)',
- plot_bgcolor='rgb(248, 248, 255)',
+ paper_bgcolor='lavenderblush',
+ plot_bgcolor='lavenderblush',
margin=dict(l=120, r=10, t=140, b=80),
showlegend=False,
)
@@ -219,14 +218,14 @@ for yd, xd in zip(y_data, x_data):
xanchor='right',
text=str(yd),
font=dict(family='Arial', size=14,
- color='rgb(67, 67, 67)'),
+ color='dimgray'),
showarrow=False, align='right'))
# labeling the first percentage of each bar (x_axis)
annotations.append(dict(xref='x', yref='y',
x=xd[0] / 2, y=yd,
text=str(xd[0]) + '%',
font=dict(family='Arial', size=14,
- color='rgb(248, 248, 255)'),
+ color='white'),
showarrow=False))
# labeling the first Likert scale (on the top)
if yd == y_data[-1]:
@@ -234,7 +233,7 @@ for yd, xd in zip(y_data, x_data):
x=xd[0] / 2, y=1.1,
text=top_labels[0],
font=dict(family='Arial', size=14,
- color='rgb(67, 67, 67)'),
+ color='dimgray'),
showarrow=False))
space = xd[0]
for i in range(1, len(xd)):
@@ -243,7 +242,7 @@ for yd, xd in zip(y_data, x_data):
x=space + (xd[i]/2), y=yd,
text=str(xd[i]) + '%',
font=dict(family='Arial', size=14,
- color='rgb(248, 248, 255)'),
+ color='ghostwhite'),
showarrow=False))
# labeling the Likert scale
if yd == y_data[-1]:
@@ -251,7 +250,7 @@ for yd, xd in zip(y_data, x_data):
x=space + (xd[i]/2), y=1.1,
text=top_labels[i],
font=dict(family='Arial', size=14,
- color='rgb(67, 67, 67)'),
+ color='dimgray'),
showarrow=False))
space += xd[i]
@@ -357,9 +356,9 @@ fig.add_trace(go.Bar(
x=y_saving,
y=x,
marker=dict(
- color='rgba(50, 171, 96, 0.6)',
+ color='mediumseagreen',
line=dict(
- color='rgba(50, 171, 96, 1.0)',
+ color='seagreen',
width=1),
),
name='Household savings, percentage of household disposable income',
@@ -369,7 +368,7 @@ fig.add_trace(go.Bar(
fig.add_trace(go.Scatter(
x=y_net_worth, y=x,
mode='lines+markers',
- line_color='rgb(128, 0, 128)',
+ line_color='purple',
name='Household net worth, Million USD/capita',
), 1, 2)
@@ -385,7 +384,7 @@ fig.update_layout(
showgrid=False,
showline=True,
showticklabels=False,
- linecolor='rgba(102, 102, 102, 0.8)',
+ linecolor='gray',
linewidth=2,
domain=[0, 0.85],
),
@@ -407,8 +406,8 @@ fig.update_layout(
),
legend=dict(x=0.029, y=1.038, font_size=10),
margin=dict(l=100, r=20, t=70, b=70),
- paper_bgcolor='rgb(248, 248, 255)',
- plot_bgcolor='rgb(248, 248, 255)',
+ paper_bgcolor='lavenderblush',
+ plot_bgcolor='lavenderblush',
)
annotations = []
@@ -423,14 +422,14 @@ for ydn, yd, xd in zip(y_nw, y_s, x):
y=xd, x=ydn - 20000,
text='{:,}'.format(ydn) + 'M',
font=dict(family='Arial', size=12,
- color='rgb(128, 0, 128)'),
+ color='purple'),
showarrow=False))
# labeling the bar net worth
annotations.append(dict(xref='x1', yref='y1',
y=xd, x=yd + 3,
text=str(yd) + '%',
- font=dict(family='Arial', size=12,
- color='rgb(50, 171, 96)'),
+ font=dict(family='Arial', size=16,
+ color='mediumseagreen'),
showarrow=False))
# Source
annotations.append(dict(xref='paper', yref='paper',
@@ -439,7 +438,7 @@ annotations.append(dict(xref='paper', yref='paper',
'(2015), Household savings (indicator), ' +
'Household net worth (indicator). doi: ' +
'10.1787/cfc6f499-en (Accessed on 05 June 2015)',
- font=dict(family='Arial', size=10, color='rgb(150,150,150)'),
+ font=dict(family='Arial', size=10, color='gray'),
showarrow=False))
fig.update_layout(annotations=annotations)